Engineering Manager

Core Responsibilities Technical Leadership & Architecture Own product architecture, including AI/LLM-integrated components Design scalable, secure, and maintainable systems Lead decisions involving: o LLM integration (OpenAI, Azure OpenAI, etc.) o RAG architectures and vector databases o AI orchestration frameworks (LangChain, Semantic Kernel, LlamaIndex) Ensure system reliability, observability, and cost efficiency Establish AI governance and safe usage practices AI Framework & Methodology Expertise Apply modern AI methodologies, including: o Retrieval-Augmented Generation (RAG) o Prompt engineering and evaluation o AI output validation and guardrails o Human-in-the-loop workflows o Model monitoring and performance evaluation Drive experimentation, A/B testing, and telemetry-based decision making Team Leadership Lead and mentor developers and QA engineers Raise AI literacy across the team Establish AI-native coding and review standards Balance speed, quality, and architectural integrity Delivery & Outcome Ownership Own predictable, high-quality releases Ensure AI features are measurable, validated, and production-ready Act as technical escalation point Drive cross-team alignment with Product, Data, and DevOps AI-Driven Engineering Excellence Leverage AI-assisted development tools to improve velocity Optimize AI cost-performance tradeoffs Embed automation into testing and CI/CD pipelines

Desired Candidate Profile

Required Qualifications 7+ years software engineering experience, 2+ years in technical leadership Hands-on experience building and deploying AI-enabled systems Strong knowledge of: o LLM integration and prompt design o RAG architectures and vector search o AI orchestration frameworks o Cloud platforms (Azure, AWS, or GCP) Experience designing scalable distributed systems Preferred Experience in regulated industries AI governance and compliance knowledge Model lifecycle management and monitoring tools